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Data & AnalyticsHybrid

Senior Analytics Engineer

DDN · Hybrid

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Last seen by MeritLog September 10, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from DDN's Ashby job board and last checked it on September 10, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model
Hybrid
Salary
Not listed by source
Location
New York Office

Hiring context

How this role compares at DDN

DDN has 96 live roles in MeritLog’s catalog across 9 job families, and 20 of them are in data & analytics. 20 of those listings publish a pay range, a disclosure rate of 21%.

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What they're asking for

  • 5+ years in analytics engineering, data engineering, or a similar data-focused roleExperience
  • Expert-level SQL including experience with complex joins, window functions, CTEs, and performance tuningSkill
  • Strong experience with dbt for building and maintaining transformation pipelinesSkill
  • Hands-on experience with a cloud data warehouse (BigQuery, Snowflake, Redshift, or similar)Skill
  • Understanding of dimensional modeling and data warehouse design patternsSkill
  • Experience building and maintaining BI content (dashboards, data models, semantic layers) in tools like Sigma, Looker, or similarSkill
  • Strong Python skills for data analysis, automation, or pipeline workSkill
  • Solid understanding of data quality practices including testing, monitoring, documentationSkill
  • Strong communication skills and demonstrated ability to translate technical concepts for business stakeholdersSkill
  • Bachelor’s degree in a quantitative field or equivalent practical experienceEducation
  • Experience with Sigma Computing specificallySkillPreferred
  • Familiarity with data quality frameworks (e.g., Elementary, Great Expectations)SkillPreferred
  • Familiarity with data governance practices - PII handling, access controls, documentation standardsSkillPreferred
  • Experience with version-controlled, CI/CD-driven analytics workflowsSkillPreferred
  • Prior experience in a small data team where you wore multiple hatsSkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

We’re looking for a Senior Analytics Engineer to own the transformation and modeling layer of DDN’s enterprise data platform. You’ll turn raw data from Salesforce, Workday, product systems, and other sources into trusted, well-documented datasets that stakeholders across Sales, Finance, Product, and Operations actually use to make decisions. You’ll work closely with data engineers who manage ingestion and infrastructure, and with analysts and business partners who consume what you build. What You’ll Own - Data modeling - design, build, and maintain dbt models that transform raw data into clean, reliable datasets for analytics and reporting - Data quality - implement and maintain testing, monitoring, and documentation so stakeholders can trust what they’re looking at - BI & semantic layer - build and maintain Sigma data models and workbooks that give business users self-serve access to data - Collaboration - partner with business stakeholders to understand their analytical needs and translate them into scalable, maintainable data models; work with data engineers on source data requirements Your Experience Includes - 5+ years in analytics engineering, data engineering, or a similar data-focused role - Expert-level SQL including experience with complex joins, window functions, CTEs, and performance tuning - Strong experience with dbt for building and maintaining transformation pipelines - Hands-on experience with a cloud data warehouse (BigQuery, Snowflake, Redshift, or similar) - Understanding of dimensional modeling and data warehouse design patterns - Experience building and maintaining BI content (dashboards, data models, semantic layers) in tools like Sigma, Looker, or similar - Strong Python skills for data analysis, automation, or pipeline work - Solid understanding of data quality practices including testing, monitoring, documentation - Strong communication skills and demonstrated ability to translate technical concepts for business stakeholders - Bachelor’s degree in a quantitative field or equivalent practical experience Nice to Have - Experience with Sigma Computing specifically - Familiarity with data quality frameworks (e.g., Elementary, Great Expectations) - Familiarity with data governance practices - PII handling, access controls, documentation standards - Experience with version-controlled, CI/CD-driven analytics workflows - Prior experience in a small data team where you wore multiple hats

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